Who You Are And Where You Live: How Race And Geography Affect The Treatment Of Medicare Beneficiaries

Abstract

There is no simple story that explains the regional patterns of racial disparities in health care.by Katherine Baicker, Amitabh Chandra, Jonathan S. Skinner, and John E. Wennberg ABSTRACT: The existence of overall racial and ethnic disparities in health care is well documented, but this average effect masks variation across regions and types of care. Medicare claims data are used to document the extent of these variations. Regions with high racial disparities in one procedure are not more likely to be high in other procedures. Unusually large racial disparities in surgery are often the result of high white rates rather than low black rates. Differences in end-of-life care are driven more by residence than by race. Policies should focus on getting the rates right, rather than solely on racial differences.T h e r e i s an e x t e n s i v e l i t e r at u r e documenting racial and ethnic disparities in the use of health care in the United States. A recent Institute of Medicine (IOM) report concluded that there are large, significant disparities in the quality and quantity of health care received by minority groups. 1 Most studies have used national samples to study racial disparities in health care, so their results represent an average across U.S. regions. Other studies extrapolate from the experiences of a single area or a single hospital. 2 One might reasonably infer from these studies' findings that racial and ethnic disparities in health care use are pervasive in every region and for all types of care. However, recent studies have shown that overall national differences mask sizable variation across regions and across procedures in racial and ethnic disparities in utilization rates.

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Diffusion of surgical innovation among patients with kidney cancer

“…33,34 The finding that the percentage of provider-attributable and tumor characteristics as well as surgeon nephrectomy case volume (the residual intraclass correlation coefficient). The denominator for calculation of this proportion includes the residual variance attributable to the surgeon random effect (after adjustment for patient demographics, comorbidity, tumor size, and surgeon case volume) and the variance attributable to unmeasured patient or tumor variables plus error.…”